000			01612nam a2200301 a 4500
005			20250918170639.0
008			120924s2012 enka b 001 0 eng
020			_a9781848212404 (hbk.) _cRM439.27
039		9	_a201211061226 _bzabidah _c201210170933 _drosli _c201209240940 _didah _y09-24-2012 _zidah
040			_aDLC _cDLC _dUKM
090			_aTA1637.S736 3
090			_aTA1637 _b.S736 3
245	0	0	_aStochastic geometry for image analysis / _cedited by Xavier Descombes.
260			_aLondon : _bWiley, _c2012.
300			_ax, 345 p. : _bill. ; _c24 cm
504			_aIncludes bibliographical references and index.
520			_a'This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling'-- _cProvided by publisher.
650		0	_aImage processing _xStatistical methods.
650		0	_aStochastic geometry.
700	1		_aDescombes, Xavier.
907			_a.b15478488 _b2019-11-12 _c2019-11-12
942			_c01 _n0 _kTA1637.S736 3
914			_avtls003513296
990			_ark4
991			_aFakulti Kejuruteraan dan Alam Bina
998			_al _b2012-11-09 _cm _da _feng _genk _y0 _z.b15478488
999			_c531012 _d531012